Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Near-surface PM2.5 prediction combining the complex network characterization and graph convolution neural network
Guyu Zhao, Hongdou He, Yifang Huang, et al.
Neural Computing and Applications (2021) Vol. 33, Iss. 24, pp. 17081-17101
Closed Access | Times Cited: 20

Showing 20 citing articles:

Deep Spatio-Temporal Graph Network with Self-Optimization for Air Quality Prediction
Xuebo Jin, Zhong-Yao Wang, Jianlei Kong, et al.
Entropy (2023) Vol. 25, Iss. 2, pp. 247-247
Open Access | Times Cited: 60
Deep-learning architecture for PM2.5 concentration prediction: A review
Shiyun Zhou, Wei Wang, Long Zhu, et al.
Environmental Science and Ecotechnology (2024) Vol. 21, pp. 100400-100400
Open Access | Times Cited: 18
A systematic survey of air quality prediction based on deep learning
Zhen Zhang, Shiqing Zhang, Caimei Chen, et al.
Alexandria Engineering Journal (2024) Vol. 93, pp. 128-141
Open Access | Times Cited: 16
Ada-STGMAT: An adaptive spatio-temporal graph multi-attention network for intelligent time series forecasting in smart cities
Xuebo Jin, Hui-Jun Ma, Jingyi Xie, et al.
Expert Systems with Applications (2025) Vol. 269, pp. 126428-126428
Closed Access | Times Cited: 2
Graph Neural Network for Air Quality Prediction: A Case Study in Madrid
Ditsuhi Iskandaryan, Francisco Ramos, Sergio Trilles
IEEE Access (2023) Vol. 11, pp. 2729-2742
Open Access | Times Cited: 22
Dynamic graph convolution neural network based on spatial-temporal correlation for air quality prediction
Ao Dun, Yuning Yang, Fei Lei
Ecological Informatics (2022) Vol. 70, pp. 101736-101736
Closed Access | Times Cited: 27
Enhancing Air Quality Forecasting: A Novel Spatio-Temporal Model Integrating Graph Convolution and Multi-Head Attention Mechanism
Yumeng Wang, Ke Liu, Yuejun He, et al.
Atmosphere (2024) Vol. 15, Iss. 4, pp. 418-418
Open Access | Times Cited: 4
TEMDI: A Temporal Enhanced Multisource Data Integration model for accurate PM2.5 concentration forecasting
Ke Ren, Kangxu Chen, Chengyao Jin, et al.
Atmospheric Pollution Research (2024) Vol. 15, Iss. 11, pp. 102269-102269
Closed Access | Times Cited: 4
Time-Series Data-Driven PM2.5 Forecasting: From Theoretical Framework to Empirical Analysis
Chengqian Wu, Ruiyang Wang, Siyu Lu, et al.
Atmosphere (2025) Vol. 16, Iss. 3, pp. 292-292
Open Access
STF-Net: An improved depth network based on spatio-temporal data fusion for PM2.5 concentration prediction
Xiaoxia Zhang, Hao Gan
Future Generation Computer Systems (2023) Vol. 144, pp. 37-49
Closed Access | Times Cited: 10
A long-term prediction method for PM2.5 concentration based on spatiotemporal graph attention recurrent neural network and grey wolf optimization algorithm
Chen Zhang, Shengzhao Wang, Yue Wu, et al.
Journal of environmental chemical engineering (2023) Vol. 12, Iss. 1, pp. 111716-111716
Closed Access | Times Cited: 10
Adaptive scalable spatio-temporal graph convolutional network for PM2.5 prediction
Qingjian Ni, Yuhui Wang, Jiayi Yuan
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107080-107080
Closed Access | Times Cited: 9
Long-term Prediction Method for PM2.5 Concentration Using Edge Channel Graph Attention Network and Gating Closed-form Continuous-time Neural Networks
Chen Zhang, Xiaofan Li, Hongyang Sheng, et al.
Process Safety and Environmental Protection (2024) Vol. 189, pp. 356-373
Closed Access | Times Cited: 2
AGATNet: An Adaptive Graph Attention Network for Bias Correction of CMAQ‐Forecasted PM2.5 Concentrations Over South Korea
Rijul Dimri, Yunsoo Choi, Ahmed Khan Salman, et al.
Journal of Geophysical Research Machine Learning and Computation (2024) Vol. 1, Iss. 3
Open Access | Times Cited: 1
An improved GCN–TCN–AR model for PM2.5 predictions in the arid areas of Xinjiang, China
Wenqian Chen, Xuesong Bai, Na Zhang, et al.
Journal of Arid Land (2024)
Closed Access | Times Cited: 1
A Spatiotemporal Interpolation Graph Convolutional Network for Estimating PM₂.₅ Concentrations Based on Urban Functional Zones
Xinya Chen, Yinghua Zhang, Yuebin Wang, et al.
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 61, pp. 1-14
Closed Access | Times Cited: 6
Dual-channel spatial–temporal difference graph neural network for PM$$_{2.5}$$ forecasting
Xiaocao Ouyang, Yan Yang, Shujun Zhang, et al.
Neural Computing and Applications (2022) Vol. 35, Iss. 10, pp. 7475-7494
Closed Access | Times Cited: 4
The ST-GRNN Cooperative Training Model Based on Complex Network for Air Quality Prediction
Shijie Chen, Song Wang, Yipan Liu, et al.
Lecture notes in computer science (2024), pp. 449-461
Closed Access
Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network
Xianglong Fan, Pan Gao, Li Zuo, et al.
Land (2023) Vol. 12, Iss. 10, pp. 1897-1897
Open Access | Times Cited: 1
Study and Prediction of Air Quality in Smart Cities through Machine Learning Techniques Considering Spatiotemporal Components
Ditsuhi Iskandaryan
(2023)
Open Access
Page 1

Scroll to top